---
license: mit
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: SUMMARIZING_STRESSED_MODEL
  results: []
pipeline_tag: summarization
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# SUMMARIZING_STRESSED_MODEL

This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3729
- Rouge1: 0.3318
- Rouge2: 0.0976
- Rougel: 0.2295
- Rougelsum: 0.229
- Gen Len: 68.6667

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log        | 1.0   | 3    | 2.5488          | 0.3021 | 0.0902 | 0.2175 | 0.2163    | 74.1429 |
| No log        | 2.0   | 6    | 2.3729          | 0.3318 | 0.0976 | 0.2295 | 0.229     | 68.6667 |


### Framework versions

- Transformers 4.27.2
- Pytorch 2.1.0+cu121
- Datasets 2.11.0
- Tokenizers 0.13.3